12 papers
Offline Reinforcement Learning for Rotation Profile Control in Tokamaks
Rohit Sonker, Hiro Josep Farre Kaga, Jiayu Chen +5
Tokamaks remain leading candidates for achieving practical fusion energy, yet many important control problems inside these devices are still difficult or unsolved. One such challen…
Future Forcing: Future-aware Training-free KV Cache Policy for Autoregressive Video Generation
Jiayi Luo, Qiyan Liu, Tengyang Wang +8
Autoregressive (AR) video generation has emerged as a promising paradigm for long-horizon video synthesis, where each frame is generated conditioned on previously generated tokens.…
Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark
Yang Fu, Haomin Bao, Rohit Sonker +4
Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-error on real devices is costly…
Core-Halo Decomposition: Decentralizing Large-Scale Fixed-Point Problems
Haixiang, Yang Xu, Jiefu Zhang +4
We study solving large-scale fixed-point equation \(x^\star=\bar F(x^\star)\) with decomposition. Standard strict decomposition assigns each agent a disjoint block and evaluates up…
ANO: A Principled Approach to Robust Policy Optimization
Yiheng Zhang, Yiming Wang, Kaiyan Zhao +3
Proximal Policy Optimization (PPO) dominates reinforcement learning and LLM alignment but relies on a "hard clipping" mechanism that discards valuable gradients. Conversely, uncons…
Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning
Aravind Venugopal, Jiayu Chen, Xudong Wu +3
The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. Generative world models captu…